15,362 research outputs found

    Oscillatory Tunnel Splittings in Spin Systems: A Discrete Wentzel-Kramers-Brillouin Approach

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    Certain spin Hamiltonians that give rise to tunnel splittings that are viewed in terms of interfering instanton trajectories, are restudied using a discrete WKB method, that is more elementary, and also yields wavefunctions and preexponential factors for the splittings. A novel turning point inside the classically forbidden region is analysed, and a general formula is obtained for the splittings. The result is appled to the \Fe8 system. A previous result for the oscillation of the ground state splitting with external magnetic field is extended to higher levels.Comment: RevTex, one ps figur

    Multiplicity fluctuations in heavy-ion collisions using canonical and grand-canonical ensemble

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    We report the higher order cumulants and their ratios for baryon, charge and strangeness multiplicity in canonical and grand-canonical ensembles in ideal thermal model including all the resonances. When the number of conserved quanta is small, an explicit treatment of these conserved charges is required, which leads to a canonical description of the system and the fluctuations are significantly different from the grand canonical ensemble. Cumulant ratios of total charge and net-charge multiplicity as a function of collision energies are also compared in grand canonical ensemble.Comment: 7 pages, 5 Figs, Published versio

    Spin Tunneling in Magnetic Molecules: Quasisingular Perturbations and Discontinuous SU(2) Instantons

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    Spin coherent state path integrals with discontinuous semiclassical paths are investigated with special reference to a realistic model for the magnetic degrees of freedom in the Fe8 molecular solid. It is shown that such paths are essential to a proper understanding of the phenomenon of quenched spin tunneling in these molecules. In the Fe8 problem, such paths are shown to arise as soon as a fourth order anisotropy term in the energy is turned on, making this term a singular perturbation from the semiclassical point of view. The instanton approximation is shown to quantitatively explain the magnetic field dependence of the tunnel splitting, as well as agree with general rules for the number of quenching points allowed for a given value of spin. An accurate approximate formula for the spacing between quenching points is derived

    CONFLLVM: A Compiler for Enforcing Data Confidentiality in Low-Level Code

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    We present an instrumenting compiler for enforcing data confidentiality in low-level applications (e.g. those written in C) in the presence of an active adversary. In our approach, the programmer marks secret data by writing lightweight annotations on top-level definitions in the source code. The compiler then uses a static flow analysis coupled with efficient runtime instrumentation, a custom memory layout, and custom control-flow integrity checks to prevent data leaks even in the presence of low-level attacks. We have implemented our scheme as part of the LLVM compiler. We evaluate it on the SPEC micro-benchmarks for performance, and on larger, real-world applications (including OpenLDAP, which is around 300KLoC) for programmer overhead required to restructure the application when protecting the sensitive data such as passwords. We find that performance overheads introduced by our instrumentation are moderate (average 12% on SPEC), and the programmer effort to port OpenLDAP is only about 160 LoC.Comment: Technical report for CONFLLVM: A Compiler for Enforcing Data Confidentiality in Low-Level Code, appearing at EuroSys 201

    Efficient algorithms for tensor scaling, quantum marginals and moment polytopes

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    We present a polynomial time algorithm to approximately scale tensors of any format to arbitrary prescribed marginals (whenever possible). This unifies and generalizes a sequence of past works on matrix, operator and tensor scaling. Our algorithm provides an efficient weak membership oracle for the associated moment polytopes, an important family of implicitly-defined convex polytopes with exponentially many facets and a wide range of applications. These include the entanglement polytopes from quantum information theory (in particular, we obtain an efficient solution to the notorious one-body quantum marginal problem) and the Kronecker polytopes from representation theory (which capture the asymptotic support of Kronecker coefficients). Our algorithm can be applied to succinct descriptions of the input tensor whenever the marginals can be efficiently computed, as in the important case of matrix product states or tensor-train decompositions, widely used in computational physics and numerical mathematics. We strengthen and generalize the alternating minimization approach of previous papers by introducing the theory of highest weight vectors from representation theory into the numerical optimization framework. We show that highest weight vectors are natural potential functions for scaling algorithms and prove new bounds on their evaluations to obtain polynomial-time convergence. Our techniques are general and we believe that they will be instrumental to obtain efficient algorithms for moment polytopes beyond the ones consider here, and more broadly, for other optimization problems possessing natural symmetries

    Abstract Learning Frameworks for Synthesis

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    We develop abstract learning frameworks (ALFs) for synthesis that embody the principles of CEGIS (counter-example based inductive synthesis) strategies that have become widely applicable in recent years. Our framework defines a general abstract framework of iterative learning, based on a hypothesis space that captures the synthesized objects, a sample space that forms the space on which induction is performed, and a concept space that abstractly defines the semantics of the learning process. We show that a variety of synthesis algorithms in current literature can be embedded in this general framework. While studying these embeddings, we also generalize some of the synthesis problems these instances are of, resulting in new ways of looking at synthesis problems using learning. We also investigate convergence issues for the general framework, and exhibit three recipes for convergence in finite time. The first two recipes generalize current techniques for convergence used by existing synthesis engines. The third technique is a more involved technique of which we know of no existing instantiation, and we instantiate it to concrete synthesis problems

    The Partial Visibility Representation Extension Problem

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    For a graph GG, a function ψ\psi is called a \emph{bar visibility representation} of GG when for each vertex v∈V(G)v \in V(G), ψ(v)\psi(v) is a horizontal line segment (\emph{bar}) and uv∈E(G)uv \in E(G) iff there is an unobstructed, vertical, ε\varepsilon-wide line of sight between ψ(u)\psi(u) and ψ(v)\psi(v). Graphs admitting such representations are well understood (via simple characterizations) and recognizable in linear time. For a directed graph GG, a bar visibility representation ψ\psi of GG, additionally, puts the bar ψ(u)\psi(u) strictly below the bar ψ(v)\psi(v) for each directed edge (u,v)(u,v) of GG. We study a generalization of the recognition problem where a function ψ′\psi' defined on a subset V′V' of V(G)V(G) is given and the question is whether there is a bar visibility representation ψ\psi of GG with ψ(v)=ψ′(v)\psi(v) = \psi'(v) for every v∈V′v \in V'. We show that for undirected graphs this problem together with closely related problems are \NP-complete, but for certain cases involving directed graphs it is solvable in polynomial time.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016
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